In conventional methods of X-ray imaging, attenuation depends on the type of body tissue scanned and the average energy level of the X-ray beam. The average energy level of the X-ray beam may be adjusted via an X-ray tube's energy setting. An X-ray tube's energy setting is measured in kilovolts (kV).
Conventionally, computed tomography (CT) imaging may be performed using a single energy level (referred to as single energy CT imaging) or dual energy levels (referred to as dual energy imaging). Dual energy images may be acquired using two or more scans of different energies during a single procedure or using one or more energy sources.
In conventional dual energy CT imaging, dual image data (e.g., two image data sets or two images) is sometimes referred to as volume data and is obtained using two different energy levels (e.g., 80 kV and 140 kV). Dual image data may be obtained concurrently, simultaneously or sequentially. If two different energy levels are used to acquire dual energy images, each of the two sets of image data may have different attenuation characteristics. The difference in attenuation levels allows for classification of elemental chemical compositions of imaged tissues. In other words, dual-energy CT enables contributions of different X-ray attenuation processes or materials in the CT image to be separated. As a result, standard dual-energy tissue classification techniques perform a so called material analysis or decomposition. The resulting material maps may then be used to perform explicit segmentation of anatomical structures such as osseous tissue in the case of bone removal. In this conventional method of segmentation, however, information about tissue classes included in the scan must be known beforehand in order to choose the appropriate material analysis algorithms.
As an alternative to explicit classification methods, direct volume rendering (DVR) with two dimensional transfer functions (2DTFs) may be used to explore volume data. Direct volume rendering is well known to those of skill in the art, and refers to electronic rendering of a medical image directly from data sets to thereby display visualizations of target regions of the body using multi-dimensional 3D or 4D or more dimensional data. The visualizations may include color as well as internal structures.
DVR does not require the use of intermediate graphic constructs, but may use mathematical models to classify certain structures and may use graphic constructs. Transfer function refers to a mathematical conversion of volume data to color and opacity values used to generate image data.
Conventional 2DTFs are based on data intensities and gradient magnitude for CT data acquired using a single energy level. However, conventional 2DTFs are limited by the intrinsic amount of information that a particular single-energy CT scan provides. More generally, the ability to differentiate tissue classes is restricted by the behavior of x-ray attenuations under one energy level.